The Predictive Value of Monocarboxylate Transporter 4 (MCT4) on Lung Adenocarcinoma Patients Treated with PD-1 Inhibitors.

PURPOSE: Monocarboxylate transporter 4 (MCT4) can influence the amount of lactate in the tumor microenvironment and further control cancer cell proliferation, migration, and angiogenesis. This study aimed to evaluate the predictive value of MCT4 for prognosis and immunotherapy efficacy in advanced lung adenocarcinoma (LUAD). PATIENTS AND METHODS: First, bioinformatics analysis was used to assess the relevance of MCT4 for survival and immunotherapy outcomes in LUAD. Subsequently, we performed a retrospective study involving 126 patients with stage IIIb to IV LUAD treated with programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors. MCT4 expression in LUAD tissues was detected by immunohistochemistry (IHC), then the patients were divided into high and low expression groups. The differences in the medical records of the two groups were compared using the X(2) test. Kaplan-Meier (K-M) method was used for survival analysis. Univariate and multivariate analysis were used to pinpoint independent predictors, and a nomogram was developed based on the significant factors for overall survival (OS) in the multivariate analysis. The predictive ability of the nomogram was evaluated through C-index, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: Both bioinformatics analysis and clinical study revealed that low MCT4 expression was associated with better prognosis and immunotherapy efficacy. Multivariate analysis of clinical characteristics showed that age >65 years, stage IV, high MCT4 expression, neutrophil-to-lymphocyte ratio (NLR)>3, lactate dehydrogenase (LDH)>250 (U/L) and carcinoembryonic antigen (CEA)>5 (ng/mL) were significantly associated with poor prognosis on immunotherapy. These factors were subsequently incorporated into the nomogram model. The C-index value of the model stood at 0.735 (95% CI= 0.662 ~ 0.807), indicating robust predictive performance of the model. The DCA curve showed that the model had a notable clinical application value. CONCLUSION: High expression of MCT4 is associated with poor prognosis and reduced efficacy of immunotherapy in patients with advanced LUAD.